Download Access to the Maize Genome: An Integrated Physical and Genetic Map

Resources and Opportunities
Access to the Maize Genome: An Integrated Physical and
Genetic Map1
Edward Coe*, Karen Cone, Michael McMullen, Su-Shing Chen, Georgia Davis, Jack Gardiner,
Emmanuel Liscum, Mary Polacco, Andrew Paterson, Hector Sanchez-Villeda, Cari Soderlund, and
Rod Wing
Department of Agronomy (E.C., G.D., J.G., M.M., M.P., H.S.-V.), Division of Biological Sciences (K.C., E.L.),
and Department of Computer Engineering/Computer Science (S.C.), University of Missouri, Columbia,
Missouri; Agricultural Research Service, United States Department of Agriculture, Columbia, Missouri (E.C.,
M.M., M.P.); Clemson University, Clemson, South Carolina (C.S., R.W.); and University of Georgia, Athens,
Georgia (A.P.)
STRATEGIES TO ACCESS A COMPLEX
CROP GENOME
Crop plant research is poised to make revolutionary strides including the following: cloning target
genes based on their function and/or their position
in the genome; documenting all genes and their interplay; defining and exploring all the existing genetic diversity in a species; and using functional information and syntenic relationships of genes in
closely related species to extrapolate gene function in
crop plants. The challenge, however, is to develop a
set of comprehensive and systematic resources to
facilitate these research endeavors. Genomic resources in maize (Zea mays) will undergird sequencing of the maize genome and will complement and
contribute to research in the cereals, other grasses,
and other crop plants.
For maize, developing genomics tools means facing
the daunting realities of size and complexity. At approximately 2,500 megabases, the maize genome is
comparable in size to that of humans, and the complexity is likely to be greater because of the abundance of multiple families of repetitive elements.
Thus, gaining access to the maize genome is best
tackled by following Goethe’s advice to seek entry to
the whole by going to its parts:
Willst du ins Unendliche schreiten,
Geh nur im Endlichen nach allen Seiten.
—Johann Wolfgang von Goethe
To efficiently take a genome apart and put it back
together requires a combination of genetic and physical mapping. In principle, genetic mapping serves to
subdivide and order the genome by crossing over
and recombining parts, whereas physical mapping
allows ordering of genomic fragments (parts) by determining the overlap among them. Accordingly, the
1
This research is supported by the National Science Foundation
Plant Genome Program (grant no. DBI 9872655).
* Corresponding author; e-mail [email protected]; fax
573– 882–2768.
www.plantphysiol.org/cgi/doi/10.1104/pp.010953.
components of the public effort to develop resources
to access the complete maize genome are to produce
a high-resolution genetic map densely populated
with markers; to produce, fingerprint, and assemble
a deep-coverage library of bacterial artificial chromosomes (BACs) into physical map segments; and
through molecular markers to integrate the genetic
and physical maps. The tools that are being built in
maize will provide a scaffold upon which to hang the
sequence and the gene constitution of the genome
and will link the sequence to the collected efforts of
the maize genetics community over the past century.
THE GENETIC MAP
A core resource essential for developing an integrated genetic/physical map for maize is a densely
marked, high-resolution genetic map. We have constructed a ⬎1850 marker map for the intermated
B73/Mo17 (IBM) population (Davis et al., 2001). The
parents of the population, B73 and Mo17, represent
the two major heterotic groups of U.S. maize germplasm. The IBM population consists of 304 recombinant inbred lines that underwent four rounds of random mating at the F2 stage. The additional meioses
result in a 3-fold expansion of the genetic map (Liu et
al., 1996). The combination of a large number of lines
and the map expansion generate a map resource with
approximately 17 times the order resolution power of
the prior maize map standard (UMC 98 genetic map,
Davis et al., 1999). The IBM map is populated with
⬎1,000 RFLP and ⬎850 simple sequence repeat (SSR)
markers.
In addition to the map per se, numerous related
resources are provided to the maize researcher. Seeds
of the IBM lines can be obtained from the Maize
Genetics Cooperation Stock Center (Urbana, IL). A
collateral resource resulting from map development
is numerous additional genetic markers. These markers include novel single copy RFLP probes, markers
for Mutator insertion sites, and new SSR primer sets.
Links to obtaining clones for hybridization probes,
screening images for RFLP probes, primer and
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Coe et al.
screening information for 1,800 maize SSR loci, and
mapscore data for the IBM population are available
from the Maize Genome Database (MaizeDB, http://
www.agron.missouri.edu/). Twelve hundred SSR
loci were developed by our group (Sharopova et al.,
2001). Comparative maps for SSR loci not on the IBM
map have also been constructed and displayed.
We have undertaken a number of initiatives promoting the use of the IBM map as a community
resource. A subset of 94 IBM lines has been identified
for general community use. We distribute DNA of
the 94 lines in microtitre plate format for individual
investigators to map their genes much as radiation
hybrid panel DNA is available for mammalian gene
mapping. We have implemented Web entry for submission of map score data, from which the resulting
locus positions are returned to the investigator. These
features are intended to provide the maize community at large with resources to contribute to generating comprehensive information on maize gene map
position.
THE PHYSICAL MAP
As a first step in producing a physical map, we
constructed three genomic DNA libraries in BACs
using DNA from the inbred line B73. B73 was selected because it is one of the parents of the genetic
mapping population; thus, markers mapped on the
IBM population and used to screen the BAC libraries
could provide anchors for connecting the genetic and
physical maps. To ensure deep coverage and minimal gaps in sequence representation in the libraries,
libraries were made using three different restriction
enzymes, and each library contained sufficient numbers of clones to provide severalfold coverage of the
haploid genome. Details of the three libraries are
shown in Table I. Together, the libraries represent
27-fold genome coverage.
To assemble the BACs into contigs, the clones are
fingerprinted by digesting with HindIII. The fingerprinting involves fractionating the fragments on agarose gels, scanning the gel images, digitizing them
with IMAGE software (Sanger Center, UK), and anTable I. Descriptions of maize B73 BAC libraries
Enzyme
No. of Clones
Average Insert Size
HindIIIa
EcoRIb
MboIc
230,400
110,592
110,592
137
162
167
Haploid
Equivalents
alyzing for contig formation using Fingerprint Contig (FPC) software (Soderlund et al., 2000). Contigs
are generated automatically with a cutoff value
of 10⫺12. Once all fingerprint data have been collected, the contigs will be edited manually to ensure
accuracy and consistency.
Accuracy and speed of contig assembly can be
enhanced by screening the BAC libraries with molecular markers. Resulting BAC addresses provide important anchor points for assembling individual
BACs into contigs. A variety of markers is being used
to screen the BAC libraries.
Core RFLP Markers
The 90 core RFLP markers that serve as bin landmarks on the genetic map have been used for BAC
screening. The majority (79) of the markers could be
used directly to hybridize to BAC filter sets. The rest
of the markers contained repetitive sequences that
precluded obtaining definitive addresses, pointing to
the need to develop single-copy overgo probes from
these markers.
Maize ESTs
In a partnership of our group with DuPont (Wilmington, DE) and Incyte Genomics (Palo Alto, CA), a
unigene set of approximately 10,000 maize ESTs is
being used to screen clones from the HindIII and
EcoRI BAC libraries. The unigene set was generated
by DuPont, using the publicly available maize ESTs
to seed their proprietary EST collection to define
unigene clusters containing the longest possible sequences for each gene in the set. At Incyte Genomics,
the unigene sequences were masked for repetitive
elements, overgo probes designed for each gene, and
the probes used to hybridize to filters containing
BAC DNA.
Sorghum Markers
Overgo probes derived from sorghum genomic
and cDNA clones are being used to screen the BACs.
These probes were designed from sequences that
hybridize across several cereal genomes, including
maize.
kb
12.5
7.1
7.4
a
HindIII library constructed at CUGI. Filter sets (5⫻) and clones
are available from CUGI (http://www.genome.clemson.edu/orders/).
b
EcoRI library constructed at Children’s Research Hospital of Oakland (CHORI). Filter sets (5⫻) and clones are available from CHORI
c
or from CUGI.
MboI library constructed at CHORI, in collaboration with Jo Messing. Filters and clones are available from CHORI
(http://www.chori.org/bacpac/home.htm).
10
Amplified Fragment-Length Polymorphism (AFLP) and
Miniature Inverted-Repeat Transposable Element
(MITE) Markers
An additional approach for screening the BACs is
based on a strategy recently applied to constructing
an integrated map for sorghum (Klein et al., 2000). In
this method, BAC pools are screened with multiplesite PCR markers, AFLPs, and MITEs to assign markers to specific BACs.
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Plant Physiol. Vol. 128, 2002
Access to the Maize Genome
MaizeDB serves as the clearinghouse for information about all markers and the BACs they detect. BAC
address information for each marker is then incorporated via FPC into the growing BAC contig assemblies. A Java applet (WebFPC) has been created to
display contigs on the web at http://www.genome.
clemson.edu/projects/maize/fpc/. BAC contigs are
updated monthly, and the data can be searched by
individual BAC clone, marker, or contig.
INTEGRATING THE PHYSICAL AND
GENETIC MAPS
Current estimates indicate that at least 50% of the
maize genome consists of complex arrays of
retrotransposon-like elements and that the majority
of these repetitive elements represent a small number
of related families (San Miguel et al., 1996). There are
no prior attempts to assemble a physical map for any
eukaryotic organism with this structure. The size of
the maize genome, 2,500 Mb, also contributes to the
difficulty of assembly. With the first of 83,000 of the
450,000 BAC fingerprints completed, FPC assembled
the BACs into 13,000 contigs and 9,300 singletons
(Clemson University Genomics Institute [CUGI] Web
site, August 2001). Assuming 450,000 BACs, 150 kb in
length, representing 27⫻ in coverage, and 80% overlap; fingerprinting alone is expected to result in approximately 2,000 apparent contigs (Lander and
Waterman, 1988). Complexity in assembly caused by
repetitive elements may cause that number to
increase.
It is clear the task at hand is to place large numbers
of genetically mapped anchor points against the
BACs to both coalesce contigs and order contigs on
the chromosome framework. To tie the assembled
BAC contigs to the genetic map, the BACs must be
screened with genetically mapped markers. The 90
core RFLP markers define the bin boundaries on the
genetic map and set a framework for the integrated
map. Many of the AFLP and MITE markers detected
by screening the BAC pools are polymorphic in the
IBM population and serve as genetic anchors. In
addition, the sorghum markers are useful anchoring
tools because they have all been mapped in sorghum,
most have been mapped in maize, and many crosshybridize to DNA from other cereals such as rice
(Oryza sativa), sugarcane (Saccharum officinarum), and
Pennisetum glaucum. Thus, these markers will not
only help connect the BAC contigs to the maize map,
but because of the colinearity of cereal genomes, they
will also facilitate creation of comparative maps.
Of the 10,000 ESTs that will be used to screen the
BAC libraries, we anticipate anchoring 1,000 contigs
by EST and SSR markers currently on the IBM map.
Many of these locations were determined by mapping SSRs that were derived from the public EST
sequences. We are initiating development of 2,000
single-nucleotide polymorphism markers derived
Plant Physiol. Vol. 128, 2002
from the ESTs. Once these global anchoring approaches draw the majority of contigs to the genetic
framework, directed sequencing of BACs and BAC
ends will be used to derive the source sequence for
development of additional single-nucleotide polymorphism markers to attempt to bring the physical
map to closure.
At MaizeDB, a BLAST server has been implemented to allow users to compare sequences of interest to all public maize sequences (including those
in the unigene set) to return a map location if known.
The output of such a query is a bin location, BLAST
score, and database links for more information, e.g.
MaizeDB link to map details; CUGI link to BAC
contigs; GenBank; and ZmDB (Zea mays database at
Iowa State University) links for sequence and clone
information.
Maps can be viewed at MaizeDB in three ways. For
any single map, chromosome-specific views are
available. For simultaneously looking at two genetic
maps, a comparative map viewer has been developed
by enhancing GIOT software obtained from the Rice
Genome Project (Japan). This viewer shows side-byside comparisons of similar regions of selected versions of maize maps and can be expanded to include
comparisons of maize to sorghum and rice. For comparing the maize genetic map to the developing
physical map—as marker data are obtained for the
BAC contigs—the GIOT viewer can be adapted to
allow queries by locus, marker name, or linkage
group to display the associated physical contigs.
The genomic resources being developed for maize
will serve as a skeleton upon which to hang the
sequence and the gene constitution of the genome,
and will link the sequence to a century of accumulated genetic studies by members of the maize genetics community. Genomic and genetic knowledge in
other cereals, other grasses, and other plant species
will complement the resources in maize and will be
enhanced in concert with them.
MaizeDB can be accessed at http://www.agron.
missouri.edu/, where maps, probes, primers, screening images, and lab protocols are presented.
ACKNOWLEDGMENTS
Suggestions on the manuscript from Sue Wessler, University of Georgia, are appreciated. We are grateful for the
advice and contributions of our External Advisory Committee, Sue Wessler, chair, University of Georgia; Vicki
Chandler, University of Arizona; Joe Ecker, Salk Institute;
Stan Letovsky, Cereon Genomics; and Antoni Rafalski, DuPont, for this project.
Received October 18, 2001; accepted October 18, 2001.
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